Integration of small world networks with multi-agent systems for simulating epidemic spatiotemporal transmission

This study proposes an integrated model based on small world network (SWN) and multi-agent system (MAS) for simulating epidemic spatiotemporal transmission. In this model, MAS represents the process of spatiotemporal interactions among individuals, and SWN describes the social relation network among agents. The model is composed of agent attribute definitions, agent movement rules, neighborhoods, construction of social relation network among agents and state transition rules. The construction of social relation network and agent state transition rules is essential for implementing the proposed model. The decay effects of infection “memory”, distance and social relation between agents are introduced into the model, which are unavailable in traditional models. The proposed model is used to simulate the transmission process of flu in Guangzhou City based on the swarm software platform. The integration model has better performance than the traditional SEIR model and the pure MAS based epidemic model. This model has been applied to the simulation of the transmission of epidemics in real geographical environment. The simulation can provide useful information for the understanding, prediction and control of the transmission of epidemics.